The overarching goal of this project is improved protection of human health through the advancement of risk assessment tools for engineered nanomaterials that allow translation of dose-response data and hazard rankings across in vitro and in vivo systems, between species, and across populations with unique sensitivities. We HYPOTHESIZE that using quantitative structure activity relationship models and novel in vitro and in vivo target tissue dosimetry models, in vitro hazard rankings and no adverse effect levels can be accurately scaled to in vivo for use in risk assessment. This hypothesis will be tested and missing, widely applicable dosimetry tools developed, under the following SPECIFIC AIMS: Construct, calibrate, and apply scalable models of ENP pharmacokinetics and dosimetry to translate dose-response relationships between in vitro and in vivo systems, between species, and between normal and sensitive individuals. 2): Predict in vivo hazard rankings of metal oxide nanoparticles from in vitro data using target tissue dosimetry based quantitative structure activity models and test predictions in a mouse model of pulmonary inflammafion 3): Establish and apply a dosimetry enabled framework for derivation of exposure limits for ENP using in vivo (data rich), and in vitro/quantitative structure activity (data limited) inflammation dose-response data. SIGNIFICANCE: Our contribution to the field of nanomaterial risk assessment will be the development and application of dosimetry models at multiple scales used in concert with mechanistic and dose-response data to develop more accurate predictive models of hazard and toxicity and derive exposure limits for multiple nanoparticles. This contribution is significant because through tools available to the consortium and other researchers and agencies, it will provide the first complete nanomaterial dosimetry platform for extrapolation, and an example of its use for the translafion, and interpretation of in vitro and rodent in vivo nanomaterial data for risk assessment. Thus, critical advances in the risk assessment paradigm for nanomaterials are expected, particulariy in enabling its evolufion towards a paradigm of prediction.